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Artificial Intelligence(AI)
Lecture No. 1
Disciplines which form the core of AI- inner circle Fields which draw from these disciplines- outer circle.
ExpertSystems
Robotics
NLP (Natural Language Processing)
Planning
ComputerVision
Search, Reasoning,
Learning
Agenda
Intelligence Intelligence of computer Artificial intelligence Intelligent computing Vs Conventional computing Contribution of other fields to AI History of AI Applications of AI References
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Intelligence?
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Can Intelligence be defined?
Intelligence can not be defined abstractly There are probably as many definitions of intelligence as there
are experts who study it.
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Intelligence (defination)
from "Mainstream Science on Intelligence" (1994), an editorial statement by fifty-two researchers: A very general mental capability that, among
other things, involves the ability to reason, plan, solve problems, think abstractly (conceptually), comprehend complex ideas, learn quickly and learn from experience.
(Gottfredson, L.S., 1997).
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Intelligence
from "Intelligence: Knowns and Unknowns" (1995), a report published by the Board of Scientific Affairs of the American Psychological Association: Individuals differ from one another in their
ability to understand complex ideas, to adapt effectively to the environment, to learn from experience, to engage in various forms of reasoning, to overcome obstacles by taking thought.
(Neisser, 1997) and (Perloff, 1996)
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Other definitions of intelligence
capacity for learning, reasoning, understanding, and similar forms of mental activity; aptitude (ability) in grasping truths, relationships, facts, meanings, etc.
the faculty(perceptual powers of the mind ) of understanding.
knowledge of an event, circumstance, etc., received or imparted; news; information.
the gathering or distribution of information, especially secret information
www. dictionary.com
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Intelligence (summary) Intelligence is the ability of:
abstract thought( Apart from a particular case or instance)
understanding communication (The activity of conveying
information) Reasoning (Logical thinking) Learning(Acquiring skill or knowledge) planning (Process of thinking about what to
do in the event of something happening) problem solving
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Intelligence of computer
According to the British computer scientist Alan Turing's test in (1950):“a computer would deserves to be
called intelligent if it could deceive a human into believing that it was human.”
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Artificial Intelligence?
???
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Artificial Intelligence
“A branch of a computer science which studies the development of software and hardware which simulates human intelligence”
(Dr. Ghassan Issa)
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Artificial Intelligence
AI is the part of computer science concerned with designing intelligent computer systems, that is, computer systems that exhibit the characteristics we associate with intelligence in human behavior- Understanding languages, learning, reasoning, solving problems, and so on.
(Barr and Feigenbaum, 1981)
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Other Definitions of AI ….
“AI is the study of how to make computer do things at which, at the moment, people are better”
(Rich and Knight, 1991)
“AI is the study of idea that enable computers to be intelligent”
(Patrick H. Winston)
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“AI is a collection of hard problems which can be solved by humans and other living things, but for which we don’t have good algorithms for solving”.
–e. g., understanding spoken natural language, medical diagnosis, circuit design, learning, self-adaptation, reasoning, chess playing, proving math theories, etc
Intelligent computing Vs Conventional computing
Intelligent Computing Conventional Computing
1 Does not guarantee a solution to a given problem.
1 Guarantees a solution to a given problem.
2 Results may not be reliable and consistent
2 Results are consistent and reliable.
3 Programmer does not tell the system how to solve the given problem.
3 Programmer tells the system exactly how to solve the problem
4 Can solve a range of problems in a given domain.
4 Can solve only one problem at a time in a given domain
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Intelligent computing Vs Conventional computing … Conventional:
Based on algorithms whose instructions are stored in memory and executed in sequential way.
AI Computing: Not based on algorithms but based on:
Knowledge base (symbolic representation)
Uses reasoning and inferencing over the knowledge base to search and perform pattern matching.
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Intelligent computing Vs Conventional computing …
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Contributions of other disciplines to AI Philosophy Logic, methods of reasoning, mind as physical
system, foundations of learning, language,rationality (wisdom)
Mathematics Formal representation and proof of algorithms,computation, (un)decidability, (in)tractability,probability
Economics utility, decision theory Neuroscience how do brain process information (neuron operation) Psychology 1- How do humans and animals think and act
2- phenomena of perception and motor control,experimental techniques
Computer engineering building fast computers
Control theory 1- How can artifacts (objects) operate under their own control?
2- design systems that maximize an objectivefunction over time.
Linguistics knowledge representation, grammar
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Abridged history of artificial intelligence
1941 first electric computer was developed 1943 McCulloch & Pitts:
Boolean circuit model of brain 1949 first “stored program” computer was introduced 1950 Turing proposed his “Turing Test” for
intelligence. 1955 early chess playing programs demonstrated 1956 in Dartmouth conference birth was given to:
"Artificial Intelligence" 1957 LISP(List Processing) language by
John McCarthy at MIT
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Abridged history of artificial intelligence
1965 expert system DENDRAL started at Stanford 1965 Robinson's complete algorithm for logical
reasoning 1966 expert system MACSYMA started at MIT 1969—79 Early development of knowledge-based
systems 1970 implementation of the Prolog language 1972 expert system MYCIN developed at Stanford 1972 SHRDLU natural language robot demonstrated at
MIT
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Abridged history of artificial intelligence
1980-- AI becomes an industry 1981-- Commercial NLP system “Intellect” available
from NLP group 1986-- Neural networks return to popularity 1987-- AI becomes a science 1995-- The emergence of intelligent agents 1995-2007 HLAI (Human Level AI):
AI should return to its roots of striving "machines that think, that learn”
Hays and Efros (2007) discuss the problem of filling in holes in a photograph
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Abridged history of artificial intelligence
2008--Artificial General Intelligence or AGI AGI looks for a universal algorithm for learning and
acting in any environment (Halevy et al_ 2009)
learning algorithm
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Applications of AI
Game playing General problem solving Expert system Natural language Processing Computer vision Robotics Education Others
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References
Gottfredson, L.S. (1997). "Foreword to "intelligence and social policy"" Intelligence 24 (1): 1–12. doi:10.1016/S0160-2896(97)90010-6. http://www.udel.edu/educ/gottfredson/reprints/1997specialissue.pdf.
Neisser, U.; Boodoo, G.; Bouchard Jr, T.J.; Boykin, A.W.; Brody, N.; Ceci, S.J.; Halpern, D.F.; Loehlin, J.C.; Perloff, R.; Sternberg, R.J.; Others, (1998). "Intelligence: Knowns and Unknowns". Annual Progress in Child Psychiatry and Child Development 1997 . ISBN 9780876308707. http://books.google.com/?id=gLWnmVbKdLwC&pg=PA95&dq=Intelligence:+Knowns+and+unknowns.
Perloff, R.; Sternberg, R.J.; Urbina, S. (1996). "Intelligence: knowns and unknowns". American Psychologist 51.
Dr. Ghassan Issa, Artificial intelligence, retrieved from: http://www.uop.edu.jo/issa/ai/ai-part1.htm, retrieved date: 04 Oct, 2011.
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References
Crash Course in Artificial Intelligence and Expert systems by Louise E. Frenzel.
Chapter No.1
Artificial Intelligence - A Modern Approach 3rd ed - S. Russell, P. Norvig (Prentice-Hall, 2010) WW
Chapter No.1
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The end
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